Discriminating same-mass Neutron Stars and Black Holes gravitational wave-forms

TL;DR

This paper explores a Bayesian method to distinguish between binary neutron star mergers and primordial binary black hole mergers using simulated gravitational wave-forms in noisy detector data, addressing classification challenges without relying on mass gaps.

Contribution

It introduces a Bayesian discrimination procedure applied to simulated wave-forms to differentiate neutron star and black hole mergers without mass gap assumptions.

Findings

Bayes factor effectively distinguishes merger types in simulations.

Method remains robust without electromagnetic counterparts.

Discrimination feasible even with similar mass ranges.

Abstract

Gravitational wave-forms from coalescences of binary black hole systems and binary neutron star systems with low tidal effects can hardly be distinguished if the two systems have similar masses. In the absence of discriminating power based on the gravitational wave-forms, the classification of sources into binary neutron stars, binary black holes and mixed systems containing a black hole and a neutron star can only be unambiguous when assuming the standard model of stellar evolution and using the fact that there exists a mass gap between neutron stars and black holes. This approach is however limited by its own assumptions: for instance the 2.6 solar mass object detected in the GW190814 event remains unclassified, and models of new physics can introduce new compact objects, like primordial black holes, which may have masses in the same range as neutron stars. Then, without an electromagnetic counterpart (kilonova), classifying mergers of compact objects without mass gap criteria remains a difficult task, unless the source is close enough. In what follows we investigate a procedure to discriminate a model between binary neutron star merger and primordial binary black hole merger by using a Bayes factor in simulated wave-forms that we superimpose to realistic detector noise.